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Extracting Keywords of UAVs Wireless Communication Protocols Based on Association Rules Learning

机译:基于关联规则学习的无人机无线通信协议关键词提取

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Unmanned Aerial Vehicles (UAVs) are increasingly popular. As a result of the tremendous number of UAVs, especially recreational UAVs, regulation becomes a challenge we are confronted with. Protocol reverse engineering offers a way to understand and regulate the drones effectively. Extracting keywords is an indispensable fundamental work for protocol reverse engineering. However, to the best of our knowledge, there are few works in the literature that openly address the issues of extracting keywords of UAVs communication protocols. In this paper, we propose a framework to extract keywords from the binary data collected from wireless communication channels of UAVs. Firstly, we capture the binary streams and segment into frames. And then we find frequent sequences utilizing multi-pattern matching algorithms. After that, we extract keywords based on frequency and analyze the association rules among these key words. Our experimental results show that 8-bit sequences such as 0x20, 0x60, 0x01, 0x09, 0xFF, 0x0A, 0x0D, 0x7D, 0x1F, 0x51, 0x49, etc. are keywords. And our framework identify frames of UAVs with a precision rate about 88% and a recall rate of around 87%.
机译:无人机(UAV)越来越受欢迎。由于无人机数量众多,尤其是休闲型无人机,管制成为我们面临的挑战。协议逆向工程提供了一种有效理解和调节无人机的方法。提取关键字是协议反向工程必不可少的基础工作。然而,据我们所知,文献中很少有作品公开地解决了提取无人机通信协议关键字的问题。在本文中,我们提出了一个从无人机无线通信通道收集的二进制数据中提取关键词的框架。首先,我们捕获二进制流并将其分段为帧。然后,我们利用多模式匹配算法找到了频繁的序列。之后,我们根据频率提取关键词,并分析这些关键词之间的关联规则。我们的实验结果表明,诸如0x20、0x60、0x01、0x09、0xFF,0x0A,0x0D,0x7D,0x1F,0x51、0x49等8位序列是关键字。我们的框架可以识别出无人机的框架,其准确率约为88%,召回率约为87%。

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